In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution. Kelleher explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art.

People often get confused by words like machine learning, artificial intelligence, or deep learning. Raise your hand if you are among them. I’m sure that you heard several times people talking about machine learning but you only have a vague idea of what it is or isn't. Don’t worry, you are not the only one. This book is here to help those listeners who want to understand machine learning in simple language.

This book explains machine learning, in simple English, for beginners of all levels. In this book, you will learn how machines are able to use data to learn on their own, discover how you can create sophisticated programs without the need for complex programming, and see daily applications of machine learning in action! 

It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets.

The powerful applications of AI have already transformed our daily lives. Virtual personal and home assistants (like Siri in Apple Pods and Alexa in Amazon Echo) have become everyday use products. Artificial intelligence and machine learning are closely related. They have become an important part of scientific study. It involves the study of statistical models and algorithms and the systems used for task performance. Our aim with this audiobook is to provide you a 360 degree view of the fundamentals and importance of machine learning technology for the beginners’ level.

The future of our world is evolving towards an era where interaction with machines form the foundation of most tasks we perform. In light of this, it is important to gain actionable knowledge in machine learning technologies and skills. These skills will be useful in the near future as you maneuver through different career paths. This audiobook introduces you to vast concepts in machine learning that will be important to your career. You will have learned so much about machine learning and the respective python libraries that you will use when building models all the time.

Data science helps make predictions and provides insights by using data analysis, statistics, and machine learning. A data scientist is an individual who can perform the duties of a data analyst, statistician, and a machine learning engineer. There are four main pillars of data science: domain expertise, mathematics, communication, and computer science. Once you get the hang of these four components, you will be closer to enhancing your overall understanding of data science. 

The Science of Information: From Language to Black Holes covers the exciting concepts, history, and applications of information theory in 24 challenging and eye-opening half-hour lectures taught by Professor Benjamin Schumacher of Kenyon College. A prominent physicist and award-winning educator at one of the nation’s top liberal arts colleges, Professor Schumacher is also a pioneer in the field of quantum information, which is the latest exciting development in this dynamic scientific field. 

In the years following her role as the lead author of the international best seller, Limits to Growth - the first book to show the consequences of unchecked growth on a finite planet - Donella Meadows remained a pioneer of environmental and social analysis until her untimely death in 2001. Thinking in Systems is a concise and crucial book offering insight for problem-solving on scales ranging from the personal to the global. Edited by the Sustainability Institute's Diana Wright, this essential primer brings systems thinking out of the realm of computers and equations and into the tangible world....

This book provides the first comprehensive overview of software architecture’s many aspects. Aspiring and existing architects alike will examine architectural characteristics, architectural patterns, component determination, diagramming and presenting architecture, evolutionary architecture, and many other topics. Mark Richards and Neal Ford - hands-on practitioners who have taught software architecture classes professionally for years - focus on architecture principles that apply across all technology stacks.

In a rarified world of scientific research, a revolution has been brewing. Its activists are not anarchists, but rather Nobel Laureates in physics and economics and pony-tailed graduates, mathematicians, and computer scientists from all over the world. They have formed an iconoclastic think-tank and their radical idea is to create a new science: complexity. They want to know how a primordial soup of simple molecules managed to turn itself into the first living cell--and what the origin of life some four billion years ago can tell us about the process of technological innovation today.

In The Unicorn Project, we follow Maxine, a senior lead developer and architect, as she is exiled to the Phoenix Project, to the horror of her friends and colleagues, as punishment for contributing to a payroll outage. She tries to survive in what feels like a heartless and uncaring bureaucracy and to work within a system where no one can get anything done without endless committees, paperwork, and approvals. One day, she is approached by a ragtag bunch of misfits who say they want to overthrow the existing order, to liberate developers, to bring joy back to technology work. 

Recent years have seen the introduction of concepts from the new and exciting field of complexity science that have captivated the attention of economists, sociologists, engineers, businesspeople, and many others. These include tipping points, the wisdom of crowds, six degrees of separation (or Kevin Bacon), and emergence. Complexity science can shed light on why businesses or economies succeed and fail, how epidemics spread and can be stopped, and what causes ecological systems to rebalance themselves after a disaster.

From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of human memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

Previously, computers couldn’t learn by themselves. They just did what programmers told them to. Today, we can model our brain’s learning processes and make computers actually learn new things and make smart decisions based on large amounts of data. No human is able to think about so much data at the same time. Sometimes, computers can be smarter than people! Sounds exciting? Well, Philip Pearson will tell you more! His book on machine learning is the ultimate guide to deep learning, neural networks, data science, and data analysis.